Amazon EKS - Deploying Kubernetes Cluster on AWS Cloud
AWS:
AWS (Amazon Web Services) is a comprehensive, evolving cloud computing platform provided by Amazon that includes a mixture of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS) offerings. AWS services can offer an organization tools such as compute power, database storage, and content delivery services.
What is EKS?
Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on AWS without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications.
Amazon EKS runs Kubernetes control plane instances across multiple Availability Zones to ensure high availability. Amazon EKS automatically detects and replaces unhealthy control plane instances, and it provides automated version upgrades and patching for them.
Working of Amazon EKS
The below images show how Amazon EKS works.
Steps to start Amazon EKS
Following are the steps to start Amazon EKS:
- Create an Amazon EKS cluster with the AWS Management Console or AWS CLI or with one of the AWS SDKs.
- Launch the worker node which registers the Amazon EKS cluster.
- An AWS CloudFormation template can be provisioned that helps configure the nodes automatically.
- When the cluster is ready, the user can configure it with the Kubernetes tools which are required for their application to communicate with their cluster.
- This Amazon EKS cluster can be used to deploy and manage applications in the same manner as one would do with any other Kubernetes environment.
A Kubernetes cluster can be created in two ways:
- With eksctl: This can be used to install the resources which are required to begin working with Amazon EKS ‘eksctl’. The ‘eksctl’ is a simple command-line utility that can be used to create and manage the Kubernetes cluster on Amazon EKS. This is considered to be one of the quickest and simplest methods of creating a cluster with Amazon EKS.
- With the AWS Management Console: This method can be used to create the resources required to start working with Amazon EKS with the help of the AWS Management Console. In this method, the user has to manually create every resource in the Amazon EKS or AWS CloudFormation console. This is considered as a much complicated and time-consuming method of creating and working with Amazon EKS.
CREATING A KUBERNETES CLUSTER USING AWS EKS:
- Configure AWS on CLI
2. Although, we can create clusters using AWS command it doesn't provide many options further. Thus, we will use eksctl for creating a cluster.
eksctl is a simple CLI tool for creating clusters on EKS - Amazon's new managed Kubernetes service for EC2. It is written in Go, uses CloudFormation, was created by Weaveworks and it welcomes contributions from the community.
For downloading refer to https://github.com/weaveworks/eksctl
Therefore, set up the path in system variables and check it's version.
3. Create a cluster.yml file to create the cluster on Amazon EKS.
apiVersion: eksctl.io/v1alpha5 kind: ClusterConfig metadata: name: lwcluster region: ap-south-1 nodeGroups: - name: ng1 desiredCapacity: 1 instanceType: t2.micro ssh: publicKeyName: ec2_key - name: ng2 desiredCapacity: 1 instanceType: t2.micro ssh: publicKeyName: ec2_key - name: ng3 minSize: 1 maxSize: 3 ssh: publicKeyName: ec2_key instancesDistribution: maxPrice: 0.017 instanceTypes: ["t2.micro"] # At least one instance type should be specified onDemandBaseCapacity: 0 onDemandPercentageAboveBaseCapacity: 50 spotInstancePools: 2
4. To launch the cluster on EKS, run the following command.eksctl create cluster -f cluster.yml
eksctl create cluster -f cluster.yml
5. To check if the cluster is created or not, run the following command.
6. Update the kubeconfig file so that kubectl command can work and we can connect to cluster from the outside world. So, run the following command.
aws eks update-kubeconfig --name lwcluster
7. Now, kubectl is connected to the EKS cluster we created on AWS.
DEPLOYING WORDPRESS AND MYSQL MULTI-TIER ARCHITECTURE ON TOP OF THE EKS CLUSTER:
- Create wordpress-deployment.yaml file with the following code snippet.
apiVersion: v1 kind: Service metadata: name: wordpress labels: app: wordpress spec: ports: - port: 80 selector: app: wordpress tier: frontend type: LoadBalancer --- apiVersion: v1 kind: PersistentVolumeClaim metadata: name: wp-pv-claim labels: app: wordpress spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi --- apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2 kind: Deployment metadata: name: wordpress labels: app: wordpress spec: selector: matchLabels: app: wordpress tier: frontend strategy: type: Recreate template: metadata: labels: app: wordpress tier: frontend spec: containers: - image: wordpress:4.8-apache name: wordpress env: - name: WORDPRESS_DB_HOST value: wordpress-mysql - name: WORDPRESS_DB_PASSWORD valueFrom: secretKeyRef: name: mysql-pass key: password ports: - containerPort: 80 name: wordpress volumeMounts: - name: wordpress-persistent-storage mountPath: /var/www/html volumes: - name: wordpress-persistent-storage persistentVolumeClaim: claimName: wp-pv-claim
2. Create mysql-deployment.yaml file with the following code snippet.
apiVersion: v1 kind: Service metadata: name: wordpress-mysql labels: app: wordpress spec: ports: - port: 3306 selector: app: wordpress tier: mysql clusterIP: None --- apiVersion: v1 kind: PersistentVolumeClaim metadata: name: mysql-pv-claim labels: app: wordpress spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi --- apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2 kind: Deployment metadata: name: wordpress-mysql labels: app: wordpress spec: selector: matchLabels: app: wordpress tier: mysql strategy: type: Recreate template: metadata: labels: app: wordpress tier: mysql spec: containers: - image: mysql:5.6 name: mysql env: - name: MYSQL_ROOT_PASSWORD valueFrom: secretKeyRef: name: mysql-pass key: password ports: - containerPort: 3306 name: mysql volumeMounts: - name: mysql-persistent-storage mountPath: /var/lib/mysql volumes: - name: mysql-persistent-storage persistentVolumeClaim: claimName: mysql-pv-claim
3. Create kustomization.yaml file with the following code snippet.
apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization secretGenerator: - name: mysql-pass literals: - password=redhat resources: - mysql-deployment.yaml - wordpress-deployment.yaml
4. Run the following command to deploy.
5. To access the WordPress site on your browser, use the URL given by LoadBalancer.
Deploying Jenkins using HELM.
Helm helps you manage Kubernetes applications — Helm Charts helps you define, install, and upgrade even the most complex Kubernetes application. Charts are easy to create, version, share, and publish — so start using Helm and stop the copy-and-paste.
Tiller is the service that actually communicates with the Kubernetes API to manage our Helm packages. A companion server component, tiller, that runs on your Kubernetes cluster, listens for commands from the helm , and handles the configuration and deployment of software releases on the cluster.
1.Set up the path for helm and tiller in system variables.
2. Run the following commands.
# helm init # helm repo add stable https://kubernetes-charts.storage.googleapis.com/ # helm repo list # helm repo update # kubectl -n kube-system create serviceaccount tiller # kubectl create clusterrolebinding tiller --clusterrole cluster-admin --serviceaccount=kube-system:tiller # helm init --service-account tiller
# kubectl get pods --namespace kube-system
3. Launch Jenkins on EKS using following command.
4. To access the Jenkins WebUI, we need to port-forward the pod.
5. To get the password of jenkin's admin from secret, we need the run the following command.
6. The password stored in the secret is 64-base-encoded. So, first decode it and then login to Jenkins's WebUI.
7. Now, we can log-in and access Jenkins running on our EKS cluster and deployed using HELM.
AWS Fargate
AWS Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). Fargate makes it easy for you to focus on building your applications. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design.
Fargate allocates the right amount of compute, eliminating the need to choose instances and scale cluster capacity. You only pay for the resources required to run your containers, so there is no over-provisioning and paying for additional servers. Fargate runs each task or pod in its own kernel providing the tasks and pods their own isolated compute environment. This enables your application to have workload isolation and improved security by design. This is why customers such as Vanguard, Accenture, Foursquare, and Ancestry have chosen to run their mission-critical applications on Fargate.
If we want to create cluster on EKS using AWS Fargate, use the following code snippet.
apiVersion: eksctl.io/v1alpha5 kind: ClusterConfig metadata: name: fargate-lwcluster region: ap-southeast-1 fargateProfiles: - name: fargate-default selectors: - namespace: kube-system
- namespace: default
I hope this article was beneficial for you. Hope you like it!
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